From a4d964c4f017fbb4050eac0a3405d392c57717f9 Mon Sep 17 00:00:00 2001
From: Sander Roosendaal <sanderroosendaal@proton.me>
Date: Sun, 14 Apr 2024 16:49:38 +0200
Subject: [PATCH] polarized marker workouts chart

---
 rowers/interactiveplots.py | 51 ++++++++++++++------------------------
 1 file changed, 19 insertions(+), 32 deletions(-)

diff --git a/rowers/interactiveplots.py b/rowers/interactiveplots.py
index 356f4f7e..38782b76 100644
--- a/rowers/interactiveplots.py
+++ b/rowers/interactiveplots.py
@@ -559,20 +559,20 @@ def goldmedalscorechart(user, startdate=None, enddate=None):
     testduration = [
         w.goldmedalseconds if w.rankingpiece else 0 for w in markerworkouts]
 
-    df = pd.DataFrame({
+    df = pl.DataFrame({
         'id': outids,
         'date': dates,
         'testpower': testpower,
         'testduration': testduration,
     })
-    df.sort_values(['date'], inplace=True)
+    df = df.sort('date')
+    df = df.drop_nulls()
 
-    mask = df['testpower'].isnull()
-    dates = df.mask(mask)['date'].dropna().values
-    testpower = df.mask(mask)['testpower'].dropna().values
-    ids = df.mask(mask)['id'].dropna().values
-
-    outids = df.mask(mask)['id'].dropna().unique()
+    dates = df['date']
+    testpower = df['testpower']
+    ids = df['id']
+    
+    outids = ids.unique()
 
     # all workouts
     alldates, alltestpower, allduration, allids = all_goldmedalstandards(
@@ -614,7 +614,7 @@ def goldmedalscorechart(user, startdate=None, enddate=None):
         duration.append(np.nan)
         workoutid.append(0)
 
-    df = pd.DataFrame({
+    df = pl.DataFrame({
         'markerscore': markerscore,
         'markerduration': markerduration,
         'score': score,
@@ -623,32 +623,20 @@ def goldmedalscorechart(user, startdate=None, enddate=None):
         'id': workoutid,
     })
 
-    df['url'] = df['id'].apply(lambda x: settings.SITE_URL +
-                               '/rowers/workout/{id}/'.format(id=encoder.encode_hex(x)))
-    df['workout'] = df['id'].apply(lambda x: workoutname(x))
+    df = df.with_columns((pl.col("id").apply(lambda x: settings.SITE_URL +
+                               '/rowers/workout/{id}/'.format(id=encoder.encode_hex(x)))).alias("url"))
+    df = df.with_columns((pl.col("id").apply(lambda x: workoutname(x))).alias("workout"))
 
-    df.sort_values(['date'], inplace=True)
+    df = df.sort('date')
 
     # find index values where score is max
-    idx = df.groupby(['date'])['score'].transform(max) == df['score']
-    df = df[idx]
+    dfmax = df.group_by("date", maintain_order=True).max()
+    dfmax = dfmax.fill_nan(0)
+    dfmax = dfmax.with_columns((pl.col("date").apply(lambda x: x.strftime("%Y-%m-%d"))).alias("date"))
+    dfmax = dfmax.with_columns((pl.col("duration").apply(lambda x: totaltime_sec_to_string(x, shorten=True))).alias("duration"))
+    dfmax = dfmax.with_columns((pl.col("markerduration").apply(lambda x: totaltime_sec_to_string(x, shorten=True))).alias("markerduration"))
 
-    df.fillna(value=0, inplace=True)
-    df['dat1'] = df['date'].map(lambda x: x.to_pydatetime(x).strftime("%Y-%m-%d"))
-
-    df2 = pd.DataFrame({
-        'markerscore': df['markerscore'],
-        'score': df['score'],
-        'markerduration':df['markerduration'].apply(
-                lambda x: totaltime_sec_to_string(x, shorten=True)),
-        'duration': df['duration'].apply(
-            lambda x: totaltime_sec_to_string(x, shorten=True)),
-        'date': df['dat1'],
-        'url':df['url'],
-        'workout':df['workout']
-    })
-
-    data_dicts = df2.to_dict("records")
+    data_dicts = dfmax.to_dicts()
     chart_data = {
         'data': data_dicts
     }
@@ -708,7 +696,6 @@ def performance_chart(user, startdate=None, enddate=None, kfitness=42, kfatigue=
     df = pd.DataFrame.from_records(records)
     if df.empty: # pragma: no cover
         return ['', 'No Data', 0, 0, 0, outids]
-    df.set_index('date', inplace=True)
 
     markerworkouts = Workout.objects.filter(
         user=user.rower, date__gte=startdate-datetime.timedelta(days=90),